Sentence examples for multivariate stepwise model from inspiring English sources

Results: In the multivariate stepwise model the strongest predictor of ultrasound estimated fetal weight was basal hepatic glucose production, followed by late gestation insulin sensitivity (total R 2 = 0.27).

Conventional variables correlated with LSR with a p value < 0.05 at first univariate analyses were used to build the final multivariate stepwise model.

In a multivariate stepwise model, age 30 40 versus <30 (aOR 0.5; 95% CI 1.02 to 0.93) remained significantly associated with shingles in the model after adjusting for PTSD.

Multivariate stepwise model selection identified ECOG status, neutrophil count, number of disease sites, time since initial diagnosis, and body mass index as significantly associated with OS (P≤0.05, Table 2).

If height and weight were co-analysed with age in a multivariate stepwise model we found that age alone performed similarly well in gender-specific and overall analysis (Table  3).

In the final multivariate stepwise model, PTSD (adjusted OR (aOR) 1.7; 95% CI 1.03 to 2.89) and CD4 <200 versus >350 cells/µL (aOR 2.4; 95% CI 1.23 to 4.81) were independently associated with reported shingles.

Multivariate stepwise models revealed that weight and height may be taken into account; however, their value added is mostly limited and depends on age-subgroup analysed.

The multivariate stepwise models further showed that except the health care workers (OR = 1.52; 95%CI 1.09-2.11), resinents in other occupations (OR = 0.06-0.67) were less likely to take up the A/H1N1 vaccination comparing with students (in Table 3).

Multivariate stepwise models were used to assess the predictive value of MMP levels compared with other potential baseline risk factors (such as, RF, nodules, CRP, ESR, HAQ, taking CVD drugs, smoking status).

Based on a multivariate stepwise logistic model, the odds' ratios for C. pneumoniae IgG antibody seropositivity, body mass index, smoking, and consumption of pickle were 3.397 (P = 0.000), 0.858 (P = 0.014), 1.692 (P = 0.012), and 5.469 (P = 0.0000), respectively.

Variables with P values < .10 were entered into a multivariate stepwise backward model.